系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (8): 2244-2253.doi: 10.12305/j.issn.1001-506X.2021.08.26

• 制导、导航与控制 • 上一篇    下一篇

基于特征匹配的舰载对陆导弹目标识别模型

谢春思1, 刘志赢2,3, 桑雨2,4   

  1. 1. 海军大连舰艇学院导弹与舰炮系, 辽宁 大连 116018
    2. 海军大连舰艇学院学员五大队, 辽宁 大连 116018
    3. 中国人民解放军91991部队, 浙江 舟山 316001
    4. 中国人民解放军91278部队, 辽宁 大连 116041
  • 收稿日期:2020-09-16 出版日期:2021-07-23 发布日期:2021-08-05
  • 作者简介:谢春思(1966—), 男, 副教授, 硕士研究生导师, 博士, 主要研究方向为导弹武器系统工程|刘志赢(1995—), 男, 硕士研究生, 主要研究方向为舰载武器装备分析与仿真|桑雨(1996—), 男, 硕士研究生, 主要研究方向为导弹的航路规划
  • 基金资助:
    国防研究项目(DJYJNKY2017-009)

Target recognition model of ship-to-land missile based on feature matching

Chunsi XIE1, Zhiying LIU2,3, Yu SANG2,4   

  1. 1. Department of Missile and ship artillery, Dalian Naval Academy, Dalian 116018, China
    2. Midshipmen Group Five, Dalian Naval Academy, Dalian 116018, China
    3. No.91991 of the PLA, Zhoushan 316001, China
    4. No.91278 of the PLA, Dalian 116041, China
  • Received:2020-09-16 Online:2021-07-23 Published:2021-08-05

摘要:

针对传统基于前视模板的匹配算法中难以直接识别与跟踪建筑等目标的问题, 提出基于特征匹配的对陆导弹目标识别模型。该模型通过对末制导导引头图像预处理, 利用改进YOLOv3深度学习目标检测算法和改进Deeplabv3+深度学习语义分割算法来识别目标区和烟雾区, 采用并行法排除烟雾遮挡对目标识别的干扰, 最终判别分析规则判断模型是否识别成功。仿真实验结果表明,该模型能够快速有效精确地完成对陆地目标的识别, 兼具较好的抗烟雾干扰能力, 有利于提高对陆导弹的目标识别水平与作战效果。

关键词: 特征匹配, 深度学习, 自动目标识别, 对陆导弹, 烟雾干扰

Abstract:

Aiming at the problem that traditional forward-looking template matching algorithm is difficult to identify and track targets such as buildings directly, a target recognition model for land missiles based on feature matching is proposed. Through prepocessing of images of terminal guidance seeker, the model takes advantage of the improved YOLOv3 deep learning target detection algorithm and Deeplabv3+deep learning semantic segmentation algorithm to recognize the target area and the smoke area. Parallel method is used to eliminate the interference of smoke occlusion on the target recognition. Finally, the discriminant analysis rule is used to judge whether the model is successfully identified. The simulation experiment results show that the model can recognize the land target quickly, effectively and accurately, which has good anti-smoke interference ability. It helps to improving the level of target recognition and combat effectiveness of the land missile.

Key words: feature matching, deep learning, automatic target recognition, land missiles, smoke jamming

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